scholarly journals Architecture and Algorithm of Formation control of Multi-unmanned vehicles Based on Swarm intelligence

2021 ◽  
Vol 1721 ◽  
pp. 012028
Author(s):  
Z Y Tian ◽  
B Su ◽  
W L Song ◽  
R Fu ◽  
P Y Lu ◽  
...  
Author(s):  
Jay T. Johnson

For the last half century scientists have been discovering the biological complexities of colonies of ants, termites, bees and other insects. Although these colonies are composed of individuals with limited physical and intellectual aptitude, the behavior of the system as a whole displays highly adaptive and intelligent behavior. As a result, in the last two decades, engineers have been pursuing methods to create artificial swarm intelligence and applying these concepts of complex swarming systems to traditional and novel engineering areas such as robotics, optimization algorithms, wireless networks, and military applications. In this paper, an overview of swarm theory research is provided, followed by a more in depth demonstration of swarm behaviors including swarm clustering, formation control and swarm motion.


2021 ◽  
Vol 9 (11) ◽  
pp. 1243
Author(s):  
Charis Ntakolia ◽  
Dimitrios V. Lyridis

Advances in robotic motion and computer vision have contributed to the increased use of automated and unmanned vehicles in complex and dynamic environments for various applications. Unmanned surface vehicles (USVs) have attracted a lot of attention from scientists to consolidate the wide use of USVs in maritime transportation. However, most of the traditional path planning approaches include single-objective approaches that mainly find the shortest path. Dynamic and complex environments impose the need for multi-objective path planning where an optimal path should be found to satisfy contradicting objective terms. To this end, a swarm intelligence graph-based pathfinding algorithm (SIGPA) has been proposed in the recent literature. This study aims to enhance the performance of SIGPA algorithm by integrating fuzzy logic in order to cope with the multiple objectives and generate quality solutions. A comparative evaluation is conducted among SIGPA and the two most popular fuzzy inference systems, Mamdani (SIGPAF-M) and Takagi–Sugeno–Kang (SIGPAF-TSK). The results showed that depending on the needs of the application, each methodology can contribute respectively. SIGPA remains a reliable approach for real-time applications due to low computational effort; SIGPAF-M generates better paths; and SIGPAF-TSK reaches a better trade-off among solution quality and computation time.


Robotica ◽  
2018 ◽  
Vol 36 (7) ◽  
pp. 1019-1047 ◽  
Author(s):  
Yuanchang Liu ◽  
Richard Bucknall

SUMMARYThe increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development.


Author(s):  
Shelley Rounds ◽  
YangQuan Chen

The main objective for this research is to design an economical and robust swarm system to achieve formation control. The system combines swarm intelligence with centroidal Voronoi tessellations (CVT) to create desired static and dynamic formations. This paper also analyzes the affect of initial starting positions and robot number on formation performance. Experiments are conducted both in simulation and on an actual mobile robot platform which show the flexible and robust nature of CVTs over other formation control algorithms.


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